555 lines
17 KiB
C++
555 lines
17 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include <iostream>
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#include <cmath>
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#include <limits>
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#include "gputest.hpp"
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#include "opencv2/core/core.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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using namespace cv;
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using namespace std;
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using namespace gpu;
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class CV_GpuArithmTest : public CvTest
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{
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public:
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CV_GpuArithmTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
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virtual ~CV_GpuArithmTest() {}
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protected:
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void run(int);
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int test(int type);
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virtual int test(const Mat& mat1, const Mat& mat2) = 0;
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int CheckNorm(const Mat& m1, const Mat& m2);
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int CheckNorm(const Scalar& s1, const Scalar& s2);
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int CheckNorm(double d1, double d2);
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};
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int CV_GpuArithmTest::test(int type)
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{
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cv::Size sz(200, 200);
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cv::Mat mat1(sz, type), mat2(sz, type);
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cv::RNG rng(*ts->get_rng());
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rng.fill(mat1, cv::RNG::UNIFORM, cv::Scalar::all(10), cv::Scalar::all(100));
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rng.fill(mat2, cv::RNG::UNIFORM, cv::Scalar::all(10), cv::Scalar::all(100));
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return test(mat1, mat2);
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}
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int CV_GpuArithmTest::CheckNorm(const Mat& m1, const Mat& m2)
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{
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double ret = norm(m1, m2, NORM_INF);
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if (ret < std::numeric_limits<double>::epsilon())
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return CvTS::OK;
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ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
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return CvTS::FAIL_GENERIC;
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}
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int CV_GpuArithmTest::CheckNorm(const Scalar& s1, const Scalar& s2)
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{
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double ret0 = CheckNorm(s1[0], s2[0]), ret1 = CheckNorm(s1[1], s2[1]), ret2 = CheckNorm(s1[2], s2[2]), ret3 = CheckNorm(s1[3], s2[3]);
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return (ret0 == CvTS::OK && ret1 == CvTS::OK && ret2 == CvTS::OK && ret3 == CvTS::OK) ? CvTS::OK : CvTS::FAIL_GENERIC;
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}
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int CV_GpuArithmTest::CheckNorm(double d1, double d2)
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{
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double ret = ::fabs(d1 - d2);
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if (ret < std::numeric_limits<double>::epsilon())
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return CvTS::OK;
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ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
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return CvTS::FAIL_GENERIC;
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}
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void CV_GpuArithmTest::run( int )
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{
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int testResult = CvTS::OK;
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try
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{
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const int types[] = {CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1};
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const char* type_names[] = {"CV_8UC1", "CV_8UC3", "CV_8UC4", "CV_32FC1"};
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const int type_count = sizeof(types)/sizeof(types[0]);
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//run tests
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for (int t = 0; t < type_count; ++t)
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{
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ts->printf(CvTS::LOG, "========Start test %s========\n", type_names[t]);
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if (CvTS::OK == test(types[t]))
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ts->printf(CvTS::LOG, "SUCCESS\n");
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else
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{
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ts->printf(CvTS::LOG, "FAIL\n");
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testResult = CvTS::FAIL_MISMATCH;
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}
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}
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}
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catch(const cv::Exception& e)
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{
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if (!check_and_treat_gpu_exception(e, ts))
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throw;
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return;
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}
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ts->set_failed_test_info(testResult);
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}
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////////////////////////////////////////////////////////////////////////////////
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// Add
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struct CV_GpuNppImageAddTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageAddTest() : CV_GpuArithmTest( "GPU-NppImageAdd", "add" ) {}
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virtual int test(const Mat& mat1, const Mat& mat2)
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::Mat cpuRes;
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cv::add(mat1, mat2, cpuRes);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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GpuMat gpuRes;
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cv::gpu::add(gpu1, gpu2, gpuRes);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// Sub
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struct CV_GpuNppImageSubtractTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageSubtractTest() : CV_GpuArithmTest( "GPU-NppImageSubtract", "subtract" ) {}
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int test( const Mat& mat1, const Mat& mat2 )
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::Mat cpuRes;
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cv::subtract(mat1, mat2, cpuRes);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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GpuMat gpuRes;
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cv::gpu::subtract(gpu1, gpu2, gpuRes);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// multiply
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struct CV_GpuNppImageMultiplyTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageMultiplyTest() : CV_GpuArithmTest( "GPU-NppImageMultiply", "multiply" ) {}
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int test( const Mat& mat1, const Mat& mat2 )
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::Mat cpuRes;
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cv::multiply(mat1, mat2, cpuRes);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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GpuMat gpuRes;
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cv::gpu::multiply(gpu1, gpu2, gpuRes);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// divide
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struct CV_GpuNppImageDivideTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageDivideTest() : CV_GpuArithmTest( "GPU-NppImageDivide", "divide" ) {}
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int test( const Mat& mat1, const Mat& mat2 )
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::Mat cpuRes;
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cv::divide(mat1, mat2, cpuRes);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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GpuMat gpuRes;
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cv::gpu::divide(gpu1, gpu2, gpuRes);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// transpose
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struct CV_GpuNppImageTransposeTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageTransposeTest() : CV_GpuArithmTest( "GPU-NppImageTranspose", "transpose" ) {}
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int test( const Mat& mat1, const Mat& )
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{
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if (mat1.type() != CV_8UC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::Mat cpuRes;
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cv::transpose(mat1, cpuRes);
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GpuMat gpu1(mat1);
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GpuMat gpuRes;
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cv::gpu::transpose(gpu1, gpuRes);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// absdiff
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struct CV_GpuNppImageAbsdiffTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageAbsdiffTest() : CV_GpuArithmTest( "GPU-NppImageAbsdiff", "absdiff" ) {}
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int test( const Mat& mat1, const Mat& mat2 )
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::Mat cpuRes;
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cv::absdiff(mat1, mat2, cpuRes);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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GpuMat gpuRes;
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cv::gpu::absdiff(gpu1, gpu2, gpuRes);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// compare
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struct CV_GpuNppImageCompareTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageCompareTest() : CV_GpuArithmTest( "GPU-NppImageCompare", "compare" ) {}
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int test( const Mat& mat1, const Mat& mat2 )
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{
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if (mat1.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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int cmp_codes[] = {CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE};
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const char* cmp_str[] = {"CMP_EQ", "CMP_GT", "CMP_GE", "CMP_LT", "CMP_LE", "CMP_NE"};
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int cmp_num = sizeof(cmp_codes) / sizeof(int);
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int test_res = CvTS::OK;
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for (int i = 0; i < cmp_num; ++i)
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{
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ts->printf(CvTS::LOG, "\nCompare operation: %s\n", cmp_str[i]);
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cv::Mat cpuRes;
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cv::compare(mat1, mat2, cpuRes, cmp_codes[i]);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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GpuMat gpuRes;
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cv::gpu::compare(gpu1, gpu2, gpuRes, cmp_codes[i]);
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if (CheckNorm(cpuRes, gpuRes) != CvTS::OK)
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// meanStdDev
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struct CV_GpuNppImageMeanStdDevTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageMeanStdDevTest() : CV_GpuArithmTest( "GPU-NppImageMeanStdDev", "meanStdDev" ) {}
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int test( const Mat& mat1, const Mat& )
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{
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if (mat1.type() != CV_8UC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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Scalar cpumean;
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Scalar cpustddev;
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cv::meanStdDev(mat1, cpumean, cpustddev);
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GpuMat gpu1(mat1);
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Scalar gpumean;
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Scalar gpustddev;
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cv::gpu::meanStdDev(gpu1, gpumean, gpustddev);
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int test_res = CvTS::OK;
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if (CheckNorm(cpumean, gpumean) != CvTS::OK)
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{
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ts->printf(CvTS::LOG, "\nMean FAILED\n");
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test_res = CvTS::FAIL_GENERIC;
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}
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if (CheckNorm(cpustddev, gpustddev) != CvTS::OK)
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{
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ts->printf(CvTS::LOG, "\nStdDev FAILED\n");
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// norm
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struct CV_GpuNppImageNormTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageNormTest() : CV_GpuArithmTest( "GPU-NppImageNorm", "norm" ) {}
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int test( const Mat& mat1, const Mat& mat2 )
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{
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if (mat1.type() != CV_8UC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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int norms[] = {NORM_INF, NORM_L1, NORM_L2};
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const char* norms_str[] = {"NORM_INF", "NORM_L1", "NORM_L2"};
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int norms_num = sizeof(norms) / sizeof(int);
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int test_res = CvTS::OK;
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for (int i = 0; i < norms_num; ++i)
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{
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ts->printf(CvTS::LOG, "\nNorm type: %s\n", norms_str[i]);
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double cpu_norm = cv::norm(mat1, mat2, norms[i]);
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GpuMat gpu1(mat1);
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GpuMat gpu2(mat2);
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double gpu_norm = cv::gpu::norm(gpu1, gpu2, norms[i]);
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if (CheckNorm(cpu_norm, gpu_norm) != CvTS::OK)
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// flip
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struct CV_GpuNppImageFlipTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageFlipTest() : CV_GpuArithmTest( "GPU-NppImageFlip", "flip" ) {}
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int test( const Mat& mat1, const Mat& )
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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int flip_codes[] = {0, 1, -1};
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const char* flip_axis[] = {"X", "Y", "Both"};
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int flip_codes_num = sizeof(flip_codes) / sizeof(int);
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int test_res = CvTS::OK;
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for (int i = 0; i < flip_codes_num; ++i)
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{
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ts->printf(CvTS::LOG, "\nFlip Axis: %s\n", flip_axis[i]);
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Mat cpu_res;
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cv::flip(mat1, cpu_res, flip_codes[i]);
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GpuMat gpu1(mat1);
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GpuMat gpu_res;
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cv::gpu::flip(gpu1, gpu_res, flip_codes[i]);
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if (CheckNorm(cpu_res, gpu_res) != CvTS::OK)
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// sum
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struct CV_GpuNppImageSumTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageSumTest() : CV_GpuArithmTest( "GPU-NppImageSum", "sum" ) {}
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int test( const Mat& mat1, const Mat& )
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{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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Scalar cpures = cv::sum(mat1);
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GpuMat gpu1(mat1);
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Scalar gpures = cv::gpu::sum(gpu1);
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return CheckNorm(cpures, gpures);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// minNax
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struct CV_GpuNppImageMinNaxTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageMinNaxTest() : CV_GpuArithmTest( "GPU-NppImageMinNax", "minNax" ) {}
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int test( const Mat& mat1, const Mat& )
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{
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if (mat1.type() != CV_8UC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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double cpumin, cpumax;
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cv::minMaxLoc(mat1, &cpumin, &cpumax);
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GpuMat gpu1(mat1);
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double gpumin, gpumax;
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cv::gpu::minMax(gpu1, &gpumin, &gpumax);
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return (CheckNorm(cpumin, gpumin) == CvTS::OK && CheckNorm(cpumax, gpumax) == CvTS::OK) ? CvTS::OK : CvTS::FAIL_GENERIC;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// LUT
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struct CV_GpuNppImageLUTTest : public CV_GpuArithmTest
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{
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CV_GpuNppImageLUTTest() : CV_GpuArithmTest( "GPU-NppImageLUT", "LUT" ) {}
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|
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int test( const Mat& mat1, const Mat& )
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|
{
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if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC3)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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|
}
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|
|
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cv::Mat lut(1, 256, CV_8UC1);
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cv::RNG rng(*ts->get_rng());
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rng.fill(lut, cv::RNG::UNIFORM, cv::Scalar::all(100), cv::Scalar::all(200));
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|
|
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cv::Mat cpuRes;
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cv::LUT(mat1, lut, cpuRes);
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|
|
|
cv::gpu::GpuMat gpuRes;
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|
cv::gpu::LUT(GpuMat(mat1), lut, gpuRes);
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|
|
|
return CheckNorm(cpuRes, gpuRes);
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|
}
|
|
};
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|
|
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/////////////////////////////////////////////////////////////////////////////
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|
/////////////////// tests registration /////////////////////////////////////
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|
/////////////////////////////////////////////////////////////////////////////
|
|
|
|
// If we comment some tests, we may foget/miss to uncomment it after.
|
|
// Placing all test definitions in one place
|
|
// makes us know about what tests are commented.
|
|
|
|
CV_GpuNppImageAddTest CV_GpuNppImageAdd_test;
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|
CV_GpuNppImageSubtractTest CV_GpuNppImageSubtract_test;
|
|
CV_GpuNppImageMultiplyTest CV_GpuNppImageMultiply_test;
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|
CV_GpuNppImageDivideTest CV_GpuNppImageDivide_test;
|
|
CV_GpuNppImageTransposeTest CV_GpuNppImageTranspose_test;
|
|
CV_GpuNppImageAbsdiffTest CV_GpuNppImageAbsdiff_test;
|
|
CV_GpuNppImageCompareTest CV_GpuNppImageCompare_test;
|
|
CV_GpuNppImageMeanStdDevTest CV_GpuNppImageMeanStdDev_test;
|
|
CV_GpuNppImageNormTest CV_GpuNppImageNorm_test;
|
|
CV_GpuNppImageFlipTest CV_GpuNppImageFlip_test;
|
|
CV_GpuNppImageSumTest CV_GpuNppImageSum_test;
|
|
CV_GpuNppImageMinNaxTest CV_GpuNppImageMinNax_test;
|
|
CV_GpuNppImageLUTTest CV_GpuNppImageLUT_test; |